ACCIDENT PRONENESS AND DRIVER LICENSE PROGRAMS

The authors believe that we should develop more absolute predictors for accident proneness, which is a negligable feat; therefore, expand driver control programs based on accident prediction at the current level of accuracy. Develop a program increasing safety and mobility. Examination of available percentage digures, which are converted to frequencies, and illumination of prediction arrors were means for expelling acceptance of accident proneness explanations. A methematical model created hyoothetical accident distributions using Spearman rho values. A survey of the literature and its data was compared with the statistical model. The model reveals reduced classification errors with higher correlations, but research reveals a negative ability to predict accidents in the driver population. Continue the systematic programs aimed at the road, the car and the normal but fallible driver. /MW/

• Corporate Authors:

  University of North Carolina, Chapel Hill

  Highway Safety Research Center
  Chapel Hill, NC  United States  27599
• Authors:
  • Campbell, B J
  • Levine, D
• Publication Date: 0

Media Info

• Features: Figures; References; Tables;
• Pagination: 11 p.

Subject/Index Terms

• TRT Terms: Driver licensing; Driver training; Forecasting; High risk drivers; Mathematical models; Statistical analysis
• Subject Areas: Data and Information Technology; Highways; Safety and Human Factors;

Filing Info

• Accession Number: 00099007
• Record Type: Publication
• Source Agency: National Safety Council Safety Research Info Serv
• Files: TRIS
• Created Date: Nov 5 1975 12:00AM